Data-driven science and engineering: machine learning, dynamical systems, and control
Data-driven science and engineering: machine learning, dynamical systems, and control
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DOI：
10.1080/00107514.2019.1665103
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发表时间：
2019-09
影响因子：
2
通讯作者：
Thomas Peters
中科院分区：
文献类型：
--
作者：
Thomas Peters
数据驱动的发现正在彻底改变我们建模、预测和控制复杂系统的方式。现在，这本教科书使用了Python和MatLab®，通过提供数据驱动方法、机器学习、应用优化以及工程数学和数学物理的经典领域日益增长的交叉的广泛概述，为下一代科学发现培训数学科学家和工程师。集中于将动态系统建模和控制与应用机器学习中的现代方法相结合，本文包括因其相关性、简单性和通用性而选择的方法。主题范围从入门到研究水平的材料，使其能够接触到来自工程和物理科学的高级本科生和初级研究生。第二版的特点是关于强化学习和物理信息机器学习的新章节，贯穿始终的重要新章节，以及章节练习。在线补充材料-包括每个部分的讲座视频、家庭作业、数据和以MatLab®、Python、Julia和R编写的代码-可在data ookuw上找到。COM。
Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering a broad overview of the growing intersection of data-driven methods, machine learning, applied optimization, and classical fields of engineering mathematics and mathematical physics. With a focus on integrating dynamical systems modeling and control with modern methods in applied machine learning, this text includes methods that were chosen for their relevance, simplicity, and generality. Topics range from introductory to research-level material, making it accessible to advanced undergraduate and beginning graduate students from the engineering and physical sciences. The second edition features new chapters on reinforcement learning and physics-informed machine learning, significant new sections throughout, and chapter exercises. Online supplementary material-including lecture videos per section, homeworks, data, and code in MATLAB®, Python, Julia, and R-available on databookuw. com.